class_docstr: This context manager makes a wrapper of input_tensor
  When created, the input_tensor is dilated,
  the input_tensor resumes to original space when exiting the context.
code: def __init__(self, input_tensor, dilation_factor):
      assert layer_util.check_spatial_dims(
          input_tensor, lambda x: x % dilation_factor == 0
      )
      self._tensor = input_tensor
      self.dilation_factor = dilation_factor
      # parameters to transform input tensor
      self.spatial_rank = layer_util.infer_spatial_rank(self._tensor)
      self.zero_paddings = [[0, 0]] * self.spatial_rank
      self.block_shape = [dilation_factor] * self.spatial_rank
  
file_path: NiftyNet/niftynet/layer/dilatedcontext.py
imports: from __future__ import absolute_import, print_function
  import tensorflow
  from niftynet.layer import layer_util
label_desc: Use image node_id 1 to create a new DilatedTensor object from inherited base classes: object with example: obj = DilatedTensor(input_tensor, dilation_factor)